U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2015–1006

Prepared in cooperation with the U.S. Army Corps of Engineers

Development of a HEC-RAS Temperature Model for the 

North Santiam River, Northwestern Oregon

Development of a HEC-RAS Temperature Model for the 

North Santiam River, Northwestern Oregon

By Adam J. Stonewall and Norman L. Buccola 

Prepared in cooperation with the U.S. Army Corps of Engineers

Open-File Report 2015–1006

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015 

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Suggested citation:

Stonewall, A.J., and Buccola, N.L., 2015, Development of a HEC-RAS temperature model for the North Santiam River, 

northwestern Oregon: U.S. Geological Survey Open-File Report 2015-1006, 26 p., 

http://dx.doi.org/10.3133/ofr20151006. 

ISSN 2331-1258 (online)
iii

Contents

Abstract ...................................................................................................................................................................... 1

Introduction................................................................................................................................................................. 1

Purpose and Scope................................................................................................................................................. 2

Background ................................................................................................................................................................ 2

Study Area .............................................................................................................................................................. 2

Methods and Data ...................................................................................................................................................... 4

Model Description ................................................................................................................................................... 4

Development of Bathymetry and Geometric Data................................................................................................... 4

Streamflow .......................................................................................................................................................... 6

Bear Branch Creek .......................................................................................................................................... 8

Rock Creek...................................................................................................................................................... 8

South Santiam River........................................................................................................................................ 8

Municipal Withdrawals ..................................................................................................................................... 8

Temperature ........................................................................................................................................................... 9

Rock Creek.......................................................................................................................................................... 9

Little North Santiam River.................................................................................................................................. 10

Bear Branch Creek and Municipal Withdrawals ................................................................................................ 10

South Santiam River.......................................................................................................................................... 10

Meteorological Data .............................................................................................................................................. 11

Model Calibration...................................................................................................................................................... 12

Streamflow............................................................................................................................................................ 13

Temperature ......................................................................................................................................................... 15

Independent Calibration Check................................................................................................................................. 18

Summary and Implications for Future Research and Monitoring .............................................................................. 23

Acknowledgements................................................................................................................................................... 26

References Cited...................................................................................................................................................... 26

Figures

Figure 1. Santiam River Study area, northwestern Oregon....................................................................................... 3

Figure 2. Example showing conversion of CE-QUAL-W2 model bathymetry to HEC-RAS model bathymetry.......... 5

Figure 3. Locations of point-source and tributary inflows, withdrawals and USGS streamgages ............................. 7

Figure 4. Measured and modeled streamflow in the North Santiam River at Mehama, Oregon 

(USGS streamgage 14183000), 2011 .................................................................................................................... 13

Figure 5. Measured and modeled streamflow in the North Santiam River at Greens Bridge, Oregon 

(USGS streamgage 14184100), 2011 .................................................................................................................... 14
iv

Figure 6. Measured and modeled streamflow in the Santiam River at Jefferson, Oregon (USGS streamgage 

14189000), 2011...................................................................................................................................................... 14

Figure 7. Measured and modeled mean daily values of temperature for the North Santiam River near 

Mehama, Oregon (USGS streamgage 14183010), 2011......................................................................................... 15

Figure 8. Measured and modeled mean daily values of temperature for the North Santiam River at 

Greens Bridge, Oregon (USGS streamgage 14184100), 2011................................................................................ 16

Figure 9. Measured and modeled mean daily values of temperature for the Santiam River near Jefferson, 

Oregon (USGS streamgage 14189050), 2011......................................................................................................... 16

Figure 10. Measured and modeled values for 2 days of hourly temperature in late August 2011 for the 

North Santiam River near Mehama, Oregon (USGS streamgage 14183010) ........................................................ 17

Figure 11. Measured and modeled streamflow for the North Santiam River at Mehama, Oregon (USGS 

streamgage 14183000), 2012.................................................................................................................................. 18

Figure 12. Measured and modeled streamflow for the North Santiam River at Greens Bridge, Oregon 

(USGS streamgage 14184100), 2012 .................................................................................................................... 19

Figure 13. Measured and modeled streamflow for the Santiam River at Jefferson, Oregon (USGS 

streamgage 14189000), 2012.................................................................................................................................. 19

Figure 14. Measured and modeled mean daily values of temperature for the North Santiam River near 

Mehama, Oregon (USGS streamgage 14183010), 2012......................................................................................... 20

Figure 15. Measured and modeled mean daily values of temperature for the North Santiam River at 

Greens Bridge, Oregon (USGS streamgage 14184100), 2012................................................................................ 20

Figure 16. Measured and modeled mean daily values of temperature for the Santiam River near 

Jefferson, Oregon (USGS streamgage 14189050), 2012 ....................................................................................... 21

Figure 17. Measured and modeled mean daily values of temperature for 2011 and 2012 at USGS

streamgages on the North Santiam River, Oregon ................................................................................................. 22

Tables

Table 1. Hydrological and meteorological stations in and near the Santiam River Basin, used for this study .......... 6

Table 2. Meteorological data time series used in the HEC-RAS model of the North Santiam River........................ 11

Table 3. Goodness-of-fit statistics for modeled hourly North Santiam River streamflows for two periods

during the 2011 calibration period............................................................................................................................ 14

Table 4. Goodness-of-fit statistics using the modeled hourly temperatures for two periods in 2011 ...................... 16

Table 5. Goodness-of-fit statistics using the modeled mean daily temperatures for two periods during 2011......... 17

Table 6. Goodness-of-fit statistics using modeled hourly streamflows for two periods in 2012. .............................. 19

Table 7. Goodness-of-fit statistics using modeled hourly temperatures for two periods in 2012 ............................ 21
v 

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

square mile (mi2) 2.590 square kilometer (km2) 

square meter (m2) 0.0002471 acre 

SI to Inch/Pound

Multiply By To obtain

cubic meter per second 0.3048 meter (m)

square mile (mi2) 2.590 square kilometer (km2) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 (NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Abbreviations and Acronyms

Name Description

CE-QUAL-W2 two-dimensional hydrodynamic and water-quality model

MAE mean absolute error

MAPE mean absolute percentage error

ME mean error

RKm river kilometer

RM river mile

RMSE root mean square error

USACE U.S. Army Corps of Engineers

USGS U.S. Geological Survey
vi 

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1 

Development of a HEC-RAS Temperature Model for the 

North Santiam River, Northwestern Oregon

By Adam J. Stonewall and Norman L. Buccola 

Abstract

A one-dimensional, unsteady streamflow and temperature model (HEC-RAS) of the North 

Santiam and Santiam Rivers was developed by the U.S. Geological Survey to be used in conjunction 

with previously developed two-dimensional hydrodynamic water-quality models (CE-QUAL-W2) of 

Detroit and Big Cliff Lakes upstream of the study area. In conjunction with the output from the 

previously developed models, the HEC-RAS model can simulate streamflows and temperatures within 

acceptable limits (mean error [bias] near zero; typical streamflow errors less than 5 percent; typical 

water temperature errors less than 1.0 °C) for the length of the North Santiam River downstream of Big 

Cliff Dam under a series of potential future conditions in which dam structures and/or dam operations 

are modified to improve temperature conditions for threatened and endangered fish. Although a twodimensional (longitudinal, vertical) CE-QUAL-W2 model for the North Santiam and Santiam Rivers 

downstream of Big Cliff Dam exists, that model proved unstable under highly variable flow conditions. 

The one-dimensional HEC-RAS model documented in this report can better simulate cross-sectionalaveraged stream temperatures under a wide range of flow conditions. 

The model was calibrated using 2011 streamflow and temperature data. Measured data were 

used as boundary conditions when possible, although several lateral inflows and their associated water 

temperatures, including the South Santiam River, were estimated using statistical models. Streamflow 

results showed high accuracy during low-flow periods, but predictions were biased low during large 

storm events when unmodeled ephemeral tributaries contributed to the actual streamflow. Temperature 

results showed low annual bias against measured data at two locations on the North Santiam River and 

one location on the Santiam River. Mean absolute errors using 2011 hourly data ranged from 0.4 to 0.7 

°C. Model results were checked against 2012 data and showed a positive bias at the Santiam River 

station (+0.6  ̊C). Annual mean absolute errors using 2012 hourly data ranged from 0.4 to 0.8 °C.

Much of the error in temperature predictions resulted from the model’s inability to accurately

simulate the full range of diurnal fluctuations during the warmest months. Future iterations of the model 

could be improved by the collection and inclusion of additional streamflow and temperature data, 

especially near the mouth of the South Santiam River. Presently, the model is able to predict hourly and 

daily water temperatures under a wide variety of conditions with a typical error of 0.8 and 0.7 °C, 

respectively. 

Introduction

The Detroit and Big Cliff Dams were constructed by the U.S. Army Corps of Engineers 

(USACE) on the North Santiam River; both dams were completed in 1953. The authorized primary 

purposes of the dams include flood risk management, hydropower, irrigation, water-quality 

improvement, recreation, and fish and wildlife habitat. Big Cliff Dam is a “re-regulating” dam that 

attenuates the highly variable flows from Detroit Dam caused by fluctuations during power generation. 
2 

The completion of the dams altered the natural hydrologic and thermal regime downstream. Winter 

streamflow peaks are smaller and summer streamflows are larger compared to pre-dam conditions. 

Water releases from the dams typically are cooler in spring and early summer, and warmer in the late 

summer and early fall, although since 2007, USACE has made operational modifications to minimize 

those thermal changes. The dams affect water temperatures for many miles downstream (Rounds, 2010). 

The North Santiam River and some of its tributaries provide habitat for Upper Willamette River 

winter steelhead (Oncorhynchus mykiss) and Chinook salmon (Oncorhynchus tshawytscha). To protect 

these fish during important life stages, the Oregon Department of Environmental Quality has set 

standards for maximum water temperatures of specific stream reaches, including the North Santiam and 

Santiam Rivers.

Previous modeling efforts have focused on determining how changes in dam operations and (or) 

changes to the elevation of water release points at Detroit Dam will affect temperatures directly 

downstream of Big Cliff Dam (Buccola and others, 2012). Although a two-dimensional hydrodynamic 

flow and temperature model (CE-QUAL-W2) was developed by Sullivan and others (2004) for the 

North Santiam and Santiam Rivers, the model proved inadequate under certain flow conditions because 

of numeric instabilities and excessive model run-times. This led to the development of a simpler, onedimensional flow and temperature model alternative for this river reach using the HEC-RAS model 

(U.S. Army Corps of Engineers, 2008). Use of this HEC-RAS model will make it possible to estimate 

the thermal effects of hypothetical dam operations and structures at Detroit and/or Big Cliff Dams 

farther downstream in the North Santiam River Basin under a wide range of conditions. 

Purpose and Scope

To inform operational and structural planning at Detroit and Big Cliff Dams, the USACE asked 

the U.S. Geological Survey (USGS) to assist with temperature modeling in the North Santiam River

Basin. The purpose of this report is to document the calibration and development of a HEC-RAS 

temperature model of the North Santiam and Santiam Rivers. The model can be used to predict 

temperatures in the North Santiam River from the outlet of Big Cliff Dam, through the confluence with 

the South Santiam River, to near the mouth of the Santiam River. Model results are intended for use in 

conjunction with previously developed temperature models of Detroit and Big Cliff Lakes (Sullivan and 

others, 2007; Buccola and others, 2012) and allow hypothetical changes at Detroit Dam to be simulated 

downstream and assessed at points along the North Santiam and Santiam Rivers. The intended use of 

the model will be to evaluate the downstream impact of changes in streamflow and temperature released 

from the Big Cliff and Detroit Dams. The HEC-RAS temperature model was calibrated using 2011 data 

and independently tested using 2012 data. 

Background

Study Area

The North Santiam River is located in northwestern Oregon (fig. 1), with headwaters in the 

Cascade Range near Duffy Lake. From there, the river flows generally northwestward to Detroit Lake, 

which is impounded by Detroit Dam. Streamflow is then re-regulated about 3 mi (5 km) downstream at 

Big Cliff Dam. From there, the North Santiam River flows generally westward until reaching its 

confluence with the Santiam River (around river mile 12 or river kilometer 19) near Jefferson, Oregon. 
3 

The Santiam River continues to the northwest, where it flows into the Willamette River just south of 

Salem, Oregon. The North Santiam River has one large tributary, the Little North Santiam River, and 

several smaller tributaries including Rock and Bear Branch Creeks. Important municipal and 

agricultural withdrawals occur near the city of Stayton, Oregon. 

Figure 1. Santiam River Study area, northwestern Oregon. 
4 

The North Santiam, South Santiam, and Santiam Rivers drain 734 mi2

 (1,903 km2), 1,040 mi2 

(2,696 km2), and 1,810 mi2 (4,692 km2) at their respective mouths (U.S. Geological Survey, 2013a). The 

Santiam River Basin has a temperate, marine climate with warm, dry summers and cool, wet winters. 

Mean precipitation in the Santiam River Basin is 78.2 in. (199 cm) (U.S. Geological Survey, 2013a). 

Seventy-one percent of the Santiam River Basin is forested. The basin area is 1.8 percent urban and 0.4 

percent impervious. North Santiam River Basin characteristics are similar to those for the entire Santiam 

River Basin (78 percent forest, 1.6 percent urban, 0.3 percent impervious). 

Methods and Data

Model Description

The North Santiam River model was created using HEC-RAS, version 4.1.0 (U.S. Army Corps 

of Engineers, 2008). HEC-RAS is a one-dimensional hydraulic model developed by the USACE at the 

Hydrologic Engineering Center (HEC). The model allows for steady and unsteady river hydraulics 

calculations, water temperature estimation, and sediment transport-mobile bed modeling (U.S. Army 

Corps of Engineers, 2014). The HEC-RAS water quality computational module is run separately, but 

uses output from the hydraulic model. Development and calibration of a HEC-RAS model consists of 

three steps:

1. Development of river bathymetry and geometric data,

2. Compiling or estimating boundary conditions, and 

3. Calibration of streamflow, water elevation, and water temperature.

Development of Bathymetry and Geometric Data 

Bathymetric data were derived from an existing CE-QUAL-W2 model of the North Santiam 

River (Sullivan and Rounds, 2004). Bathymetric data in CE-QUAL-W2 are configured in layers 

(vertical grid direction) and segments (longitudinal flow direction) and can be described by location, 

cell width, cell slope and orientation, and cell height. HEC-RAS river bathymetry was developed using 

upstream, bottom edge points of each individual CE-QUAL-W2 cell and interpolating to the bottom 

edge points of each consecutive layer, creating a HEC-RAS cross section at the most upstream point of 

each CE-QUAL-W2 segment. 

The process of constructing the HEC-RAS cross-sectional shape from the CE-QUAL-W2 cell 

geometries is best illustrated with a hypothetical example (fig. 2). In this example, the x, y, and z 

coordinates of the right bank of cell A can be determined using the latitude, longitude, and elevation of 

the center of cell A, and then applying a correction based on the orientation and width of the cell. The 

left bank of cell A can then be determined using the same procedure in the opposite direction. The banks 

of cell B are then determined by extending the distance from the center of the cell and adding the height 

of cell A to the determined elevation. The process is repeated until cell F is reached, after which the 

center of the next (downstream) cell A is determined using slope, orientation and reach length, and the 

process repeated. 
5 

Figure 2. Example showing conversion of CE-QUAL-W2 model bathymetry to HEC-RAS model bathymetry. 

Calculated HEC-RAS stream widths at 1 m of depth were compared against a database of stream 

widths between Big Cliff Dam and the Greens Bridge streamgage acquired by the USGS in the summer 

of 2002 (U.S. Geological Survey, 2013b). After calibration (see section, “Model Calibration”) the HECRAS model was run at the same streamflow as those observed during width collection in 2002 (summer 

low flow). Measured stream widths showed more variability than the model stream widths (standard 

deviations of 15.3and 12.6 m, respectively). The average model stream width was within 2 percent of 

the average measured stream width. These results suggest that the model represents average stream 

widths well, but underrepresents stream width variability. 
6 

Streamflow

When possible, boundary conditions and lateral inflows were based on measured data (table 1, 

fig. 3). When measured data were not available, streamflow values were estimated using regression 

techniques from overlapping data periods prior to 2011, or as noted. For calendar year 2011, measured 

streamflow data for upstream boundary inputs were available at North Santiam River at Niagara (USGS 

streamgage 14181500) and the Little North Santiam River near Mehama (14182500). Other inputs were 

estimated as follows. 

Table 1. Hydrological and meteorological stations in and near the Santiam River Basin, used for this study.

[Gaps in period of record are not denoted

USG stream gages Period of record

USGS ID Name Abbreviated name Lat Long Streamflow Temperature

14181500 North Santiam River at Niagara, OR Niagra 44.75 -122.30 1905–2014 1953–2014

14181750 Rock Creek near Mill City, OR Rock Creek 44.71 -122.43 2005–2008 2005–2009

14182500 Little North Santiam River near Mehama, OR Little North Santiam 44.79 -122.58 1931–2014 2000–2014

14183000 North Santiam River at Mehama, OR Mehama 44.79 -122.62 1905–2014 2000–20141

14184100 North Santiam River at Greens Bridge, near 

Jefferson, OR 

Greens Bridge 44.71 -122.97 1964–2014 1985–2014

14187200 South Santiam River near Foster, OR Foster 44.41 -122.69 1973–2014 1973–2014

14187500 South Santiam River at Waterloo, OR Waterloo 44.50 -122.82 1905–2014 1963–20142

14187600 Lebanon Santiam Canal near Lebanon, OR Lebanon Canal 44.51 -122.86 1992–2014 none

14189000 Santiam River at Jefferson, OR Jefferson 44.71 -123.01 1907–2014 1963–20143

Other 

stations

Name Abbreviated name Lat Long

Meteorological station near Jordan, OR Jordan 44.72 -122.69

University of Oregon Solar Radiation Monitoring 

Laboratory- Salem

UOSRML 44.94 -123.03

Salem Municipal Airport. Salem 44.91 -123.00

1

Temperature period of record for streamgage 14183000 includes data from nearby streamgage 14183010, North Santiam 

River near Mehama, Oregon.

2

Temperature data were not collected at streamgage 14187500 from Oct. 1, 2002, until Oct. 27, 2013.

3

Temperature period of record for station 14189000 includes data from nearby station 14189050, Santiam River near 

Jefferson, Oregon.
7 

Figure 3. Locations of point-source and tributary inflows, withdrawals and USGS streamgages.
8 

Bear Branch Creek

Streamflow at the mouth of Bear Branch Creek was estimated using the following equation: 

QBB = 0.584 ∗ QLLL (1)

where:

QBB is the streamflow at Bear Branch Creek, in cubic meters per second, and

QLNS is the streamflow at Little North Santiam streamgage (14182500), in cubic meters per second

Rock Creek

Streamflow at the mouth of Rock Creek was estimated using the following equations: 

 QRR = QLLL ∗ 0.037 + 2.28 (2)

 QRRR = QLLL ∗ 0.128 − 14.7 (3)

If QLNS ≤ 200 m3

/s, then QRC = QRCL (4)

If QLNS ≥ 1,000 m3

/s, then QRC = QRCH (5)

If 200 m3

/s < QLNS < 1,000 m3/s, then QRC = (QLNS-200)/800*(QRCH)+

(1,000-QLNS)/800*(QRCL) (6)

where:

QLNS is the streamflow at Little North Santiam, in cubic meters per second, 

QRCL is the streamflow at Rock Creek during low-flow conditions, in cubic meters per second, 

QRCH is the streamflow at Rock Creek during high-flow conditions, in cubic meters per second, and

QRC is the final estimated streamflow at Rock Creek, in cubic meters per second. 

Mean absolute percentage error (MAPE) for this regression equation is 32 percent. Errors tended 

to be highest (both MAPE and root mean-squared error [RMSE]) during flood events. 

South Santiam River

Streamflow at the mouth of the South Santiam River was estimated using the following 

equation: 

Q S = Q S ∗ 1.23 − QLL (7)

where:

QSSM is the streamflow at mouth of the South Santiam River, in cubic meters per second, 

QSSW is the streamflow at the South Santiam River at Waterloo streamgage (USGS 14187500), in cubic 

meters per second, and 

QLSC is the streamflow at the Lebanon-Santiam Canal, in cubic meters per second. 

Municipal Withdrawals

Municipal withdrawals at three locations, river mile 31.0 (rkm 49.9), 29.5 (rkm 47.5) and 19.6 

(rkm 31.6), were estimated by the Oregon Water Resources Department and used without further 

modification. 
9 

Temperature

When possible, temperature was simulated using measured data as boundary conditions. USGS 

temperature data typically are collected at well-mixed sections, and checked for lateral variation at least 

twice a year. Consequently, temperatures were assumed well-mixed at recorded cross sections, and not 

corrected. When measured data were not available, temperature values were estimated using regression 

techniques, or as noted. For calendar year 2011, measured temperature data were available at the North 

Santiam River at Niagara streamgages. Measured temperature data were used from the Little North 

Santiam River near Mehama streamgage, with a monthly warming rate adjustment applied to water 

temperature data to account for thermal differences between the streamgage and the mouth of the river. 

Rounds (2010) documented a maximum summertime warming rate of 0.11 °C/mi for streams in the 

Willamette River Basin. Little North Santiam River and other temperature inputs were estimated as 

follows: 

Rock Creek

Water temperature at the mouth of Rock Creek was estimated using the equation: 

TRR = 10(log(T )∗0.829+0.070 + 3.3 miles ∗ WW (8)

where:

TLNS is the temperature at the Little North Santiam River streamgage, in degrees Celsius, 

TRC is the temperature at the mouth of Rock Creek, in degrees Celsius, 

WR is the warming rate, in degrees Celsius per mile, using the following rates:

January: 0.02  ̊C/mi

February: 0.05  ̊C/mi

March: 0.07  ̊C/mi

April: 0.08  ̊C/mi

May: 0.09  ̊C/mi

 June–September: 0.11  ̊C/mi

October: 0.09  ̊C/mi

November: 0.05  ̊C/mi

December: 0.02  ̊C/mi
10 

Little North Santiam River

Temperature at the mouth of the Little North Santiam River was estimated using the following 

equation: 

TLLL = TLLL + 2.0 mmmmm ∗ WW (9)

where:

TLNSM is the temperature at the mouth of the Little North Santiam River, in degrees Celsius, 

TLNS is the temperature at USGS streamgage 14182500 on the Little North Santiam River, in degrees 

Celsius, 

WR is the warming rate, in degrees Celsius per mile, which is identical to the rate used for Rock Creek. 

Bear Branch Creek and Municipal Withdrawals

Temperature data for Bear Branch Creek and all municipal withdrawals were not available, and 

were assigned to be identical to those at the mouth of the Little North Santiam River. (Withdrawals were 

represented as negative inflow hydrographs in HEC-RAS, and needed an accompanying temperature 

hydrograph). 

South Santiam River

Water temperature at the mouth of the South Santiam River was estimated using the following 

equations: 

T SSS = T S + 0.4 ∗ ((0.14 ∗ T SSSS − 0.67)) (10) 

T SSSSS = T S + 0.4 ∗ ((0.22 ∗ T SSSSS − 1.04)) (11) 

T SSS = T S + 0.4 ∗ ((0.32 ∗ T SSSS − 2.00)) (12) 

II, T S = T SSSS;th e T S = T SSSS (13) 

II, T SSSS < T S < T SSSSS;th e T S = T SSSS + (T SSSSS − T SSSS) TSSS−TSSSmmm

TSSS SS −TSSS

(14) 

II, T S = T SSSSS;th e T S = T SSSSS (15) 

 II, T SSSSS < T S < T SSSS;th e T S = T SSSSS + (T SSSS − T SSSSS) TSSS−TSSS SS

TSSS SS−TSSS SS

(16) 

T SSSS;th e T S = T SSSS (17) 

where:

TSSMmin is the daily minimum temperature at the mouth of the South Santiam River, in degrees Celsius, 

TSSMmean is the daily mean temperature at the mouth of the South Santiam River, in degrees Celsius, 

TSSMmax is the daily maximum temperature at the mouth of the South Santiam River, in degrees Celsius, 

TSSF is the measured subdaily temperature of the South Santiam River at Foster, in degrees Celsius,

TSSFmin is the daily minimum temperature of the South Santiam River at Foster, in degrees Celsius, 

TSSFmean is the daily mean temperature of the South Santiam River at Foster, in degrees Celsius, and 

TSSFmax is the daily maximum temperature of the South Santiam River at Foster, in degrees Celsius. 
11 

Time of travel was not considered in this analysis. In other words, it was assumed that the 

maximum and minimum South Santiam River water temperature values occurred at the same time at 

both locations (Foster streamgage and mouth) and that the general patterns in water temperature were

identical at both locations.

Meteorological Data

Water temperature simulation using HEC-RAS requires time series of atmospheric pressure, air 

temperature, humidity, short-wave solar radiation, cloudiness, and wind speed. In HEC-RAS, 

meteorological data can be associated with one or multiple station locations around the basin. Each cell 

of the HEC-RAS model then can be assigned to a specific meteorological station, or assigned 

automatically based on distance to the nearest meteorological station. 

Initially, meteorological time series in the constructed model were allocated to one of three 

locations—the upper basin at Detroit Dam, the middle of the basin near the Jordan meteorological 

station, and the lower basin near the Salem Airport. Specific meteorological time series (for example, 

solar radiation and wind speed) not available at one location were copied from the nearest station. 

Subsequent investigations found that specific meteorological time series were not necessarily 

representative of the surrounding region. For example, whereas most of the upper North Santiam River 

is moderately narrow, with large buffers of trees on either side, wind speeds recorded at Detroit Dam 

may be more indicative of the open space around the dam. Consequently, the three meteorological 

datasets were consolidated into one dataset for the most centralized location of the three stations 

(Jordan). The sources of data for each meteorological time series are listed in table 2. 

Table 2. Meteorological data time series used in the HEC-RAS model of the North Santiam River.

Time series Location Source

Atmospheric Pressure Salem Airport MESOWEST

Air Temperature Salem Airport MESOWEST

Humidity Jordan weather station RAWS

Short Wave Radiation Jordan weather station RAWS

Cloudiness Salem Airport MESOWEST

Wind Speed Jordan weather station RAWS

referenceMesoWest http://mesowest.utah.edu/

RAWS USA Climate Archive http://www.raws.dri.edu/
12 

Two of the six time series were modified slightly for use with the model. Short-wave radiation 

was adjusted using the following equations: 

If S < 110, S = 110 (18)

If T S < 15: 00, S = S ∗ 0.8 (19) 

If T S ≥ 15: 00, S = S ∗ 0.65 (20) 

where:

SWR is short-wave solar radiation, in watts per square meter, and

TSWR is the time-of-day of the short-wave radiation measurement using a 24-hour clock, and midnight is 

represented as 00:00. 

These equations moderate the effect of short-wave radiation on stream water temperature. There 

is no algorithm in HEC-RAS version 4.1.0 to account for vegetative or topographic shading. The two 

coefficients in equations 19 and 20 are applied to the short-wave radiation time series to mimic shading 

patterns. Preliminary results indicated that more shading was needed in the afternoon to better match 

measured stream temperature data. Similarly, the minimum short-wave radiation value of 110 watts per 

square meter is designed to account for heat sources not accounted for in the HEC-RAS model, such 

inputs include internal friction, chemical and biological processes, forest radiation, condensation and 

transfer of sensible heat and the exchange of heat between the river and its bed. Evans and others (1998) 

showed that up to 24 percent of daily total energy transfer can occur at the channel bed. 

Cloudiness data also were adjusted for model use. Cloudiness data are compiled by MesoWest 

(at http://mesowest.utah.edu, accessed July 22, 2013) in three variables representing cloud coverage at 

three different elevations. The three cloudiness time series were summed into a single time series, which 

was converted into percentiles (the highest value of the year was rated as 1, the lowest value 0.) 

Resulting percentiles were entered as cloudiness values between 0 and 1 (the fraction of cloudiness). 

Model Calibration

The HEC-RAS model of the North Santiam and Santiam Rivers was calibrated using 2011 data, 

and the calibrated model was independently tested using 2012 data. 2011 and 2012 were selected for 

calibration and testing because of the relative abundance of streamflow, water temperature, and 

meteorological data available for those years.
13 

Streamflow

Streamflow was calibrated by comparing measured streamflow at the Mehama, Greens Bridge, 

and Jefferson USGS streamgages with modeled streamflow, and adjusting model parameters to 

minimize the difference between measured and modeled values of streamflow and water temperature. 

Calibration was an iterative process. Emphasis was placed on achieving the best fit to measured water 

temperatures during summer and fall (June–November), when streamflow is typically lowest and the 

river is warmest. Little calibration was necessary, with the exception of the reach downstream of the 

confluence of the North Santiam and South Santiam Rivers. Streamflow was calibrated by adjusting 

Manning’s n values (final values ranged from 0.03 to 0.07) and adjusting the contributions of ungaged 

streamflow between the South Santiam River at Waterloo streamgage (14187500) and the mouth of the 

South Santiam River. 

Measured and modeled 2011 streamflow at Mehama, Greens Bridge, and Jefferson are shown in 

figures 4, 5, and 6, respectively, with goodness-of-fit metrics listed in table 3. In general, model errors 

increase from periods of low streamflows to periods of high streamflows. Model results typically show 

a negative bias during periods of high streamflow. This is likely due, at least in part, to underrepresentation of intermittent and ephemeral streams that are not included in the model. Such streams 

provide minimal streamflow contribution during low streamflow periods, but collectively can account 

for considerable streamflow during periods of high streamflow. For example, the drainage area at the 

Greens Bridge streamgage, as estimated by the USGS, is 736 mi2

 (1,096 km2). Adding the upstream 

drainage area at the Niagara streamgage to the three largest tributaries between Niagara and Greens 

Bridge (Rock Creek, Little North Santiam River, Bear Branch Creek) sums to about 593 mi2 (1,536 

km2

), which is about 81 percent of the drainage area at Greens Bridge. Most, if not all, of these ungaged 

creeks that represent the remaining 19 percent of the drainage area upstream of Greens Bridge likely 

contribute little, if any streamflow during the dry summer and early fall. However, during moderate to 

extreme streamflow events, they likely contribute significant streamflow at the Greens Bridge 

streamgage. Because this model was designed to estimate streamflow temperatures that occur during 

periods of low streamflow (summer and fall), no effort was made to account for these ungaged 

tributaries.

Figure 4. Measured and modeled streamflow in the North Santiam River at Mehama, Oregon (USGS streamgage

14183000), 2011. 
14 

Figure 5. Measured and modeled streamflow in the North Santiam River at Greens Bridge, Oregon (USGS 

streamgage 14184100), 2011. 

Figure 6. Measured and modeled streamflow in the Santiam River at Jefferson, Oregon (USGS streamgage

14189000), 2011. 

Table 3. Goodness-of-fit statistics for modeled hourly North Santiam River streamflows for two periods during the 

2011 calibration period. 

[Abbreviations: ID, identification number; ME, mean error; MAE, mean absolute error; RMSE, root-mean squared error; MAPE, mean 

absolute percentage error; m3

/s, cubic meters per second]

Streamgage USGS ID ME MAE RMSE MAPE

(m3/s) (m3/s) (m3/s) (percent)

Calendar year 2011

Mehama 14183000 -11.0 11.3 19.1 9.6

Greens Bridge 14184100 -17.5 18.0 27.2 14.7

Jefferson 14189000 -26.7 31.8 57.7 12.4

June– October 2011

Mehama 14183000 -2.6 3.3 5.4 3.9

Greens Bridge 14184100 -4.9 5.9 9.4 7.6

Jefferson 14189000 1.3 8.1 10.2 7.5
15 

Modeled streamflow during June–November, when water temperatures typically are highest, 

suggests better agreement with measured values. MAPEs for the three locations during the dry period 

averaged about 4–8 percent. Mean errors for the three sites during the dry period averaged between 

about -5 and +1 percent, with sites upstream of the South Santiam River confluence showing a slight 

negative bias, and the comparison in the South Santiam River at the Jefferson streamgage showing a 

slight positive bias. Excellent measured streamflow data have an associated measurement error on the 

order of 5 percent for at least 95 percent of the record (Novak, 1985); therefore, this magnitude of lowflow bias in the model seems to be acceptable and should not greatly affect the water-temperature 

predictions. 

Temperature

Model predictions of water temperature were calibrated for 2011 in a similar manner to 

streamflow. Measured values at Mehama, Greens Bridge, and Jefferson were compared to modeled 

values, and model parameters were adjusted to minimize the difference between the two. Adjusted 

model parameters that had the most effect on temperature values include Manning n values (channel 

roughness coefficients, which affect time of travel and consequently time of exposure to short-wave 

solar radiation), and short-wave solar radiation inputs (see section, “Meteorological Data”). 

A comparison of measured and modeled daily average temperatures for 2011 shows that the 

model captured the weekly and seasonal patterns in the data relatively well (figs. 7, 8, and 9 for 

Mehama, Greens Bridge, and Jefferson, respectively), with goodness-of-fit metrics showing a low 

overall seasonal bias and a mean absolute error less of 0.8 °C or less (table 4). Mean error values are 0.1 

°C or less for the calendar year, suggesting little overall bias at all three sites, but a small amount of 

positive bias is present at the Greens Bridge and Jefferson sites for the warm-water period of June–

November (0.3 and 0.2°C, respectively). Mean absolute errors are fairly consistent between the entire 

calendar year and the warm-water period. The best fit occurred at the most upstream site, Mehama. 

Figure 7. Measured and modeled mean daily values of temperature for the North Santiam River near Mehama, 

Oregon (USGS streamgage 14183010), 2011. 
16 

Figure 8. Measured and modeled mean daily values of temperature for the North Santiam River at Greens Bridge, 

Oregon (USGS streamgage 14184100), 2011. 

Figure 9. Measured and modeled mean daily values of temperature for the Santiam River near Jefferson, Oregon 

(USGS streamgage 14189050), 2011. 

Table 4. Goodness-of-fit statistics using the modeled hourly temperatures for two periods in 2011. 

[Abbreviations: ID, identification number; ME, mean error; MAE, mean absolute error; RMSE, root-mean squared error; MAPE, mean 

absolute percentage error;  ̊C, degrees Celsius]

Streamgage USGS ID ME MAE RMSE MAPE

( ̊C) ( ̊C) ( ̊C) (percent)

Calendar year 2011

Mehama 14183010 -0.1 0.4 0.5 5.3

Greens Bridge 14184100 -0.1 0.7 0.9 7.7

Jefferson 14189050 0.1 0.6 0.7 6.2

June– October 2011

Mehama 14183010 0.0 0.4 0.5 3.4

Greens Bridge 14184100 0.3 0.8 1.1 5.8

Jefferson 14189000 0.2 0.6 0.8 4.5
17 

Goodness-of-fit metrics also were evaluated using daily average temperatures (table 5). Results 

are similar to those derived for the hourly temperatures in table 4, but the daily mean errors tended to be 

slightly lower. This is a reflection of the model’s tendency to better-represent average daily conditions 

than the diurnal variation of temperature. Measured and modeled hourly temperatures for a typical 

warm-weather period in 2011 at Mehama demonstrate a strong daily variation (fig. 10). The model 

adequately simulates the timing of daily temperature extremes, but tends to over-predict daily 

temperature maximums during warm conditions. 

Table 5. Goodness-of-fit statistics using the modeled mean daily temperatures for two periods during 2011. 

[Abbreviations: ID, identification number; ME, mean error; MAE, mean absolute error; RMSE, root-mean squared error; MAPE, mean

absolute percentage error;  ̊C, degrees Celsius]

Streamgage USGS ID ME MAE RMSE MAPE

( ̊C) ( ̊C) ( ̊C) (percent)

Calendar year 2011

Mehama 14183010 -0.1 0.4 0.4 4.6

Greens Bridge 14184100 -0.1 0.7 0.8 7.0

Jefferson 14189050 0.1 0.5 0.6 5.4

June– October 2011

Mehama 14183010 0.0 0.3 0.4 2.6

Greens Bridge 14184100 0.3 0.7 0.9 5.1

Jefferson 14189050 0.2 0.5 0.6 3.7

Figure 10. Measured and modeled values for 2 days of hourly temperature in late August 2011 for the North 

Santiam River near Mehama, Oregon (USGS streamgage 14183010).
18 

Independent Calibration Check

In order to check the performance of the calibrated model, the model was tested with an 

independent dataset. Boundary condition and lateral inflow data from 2012 were entered into the same 

model using the same data sources and estimation techniques, and the results were checked against 

measured data. Measured and modeled 2012 streamflows at Mehama, Greens Bridge, and Jefferson 

showed relatively good agreement for most periods (figs. 11, 12, and 13, respectively), with goodnessof-fit metrics indicating slightly higher errors relative to the 2011 statistics (table 6). Streamflow errors 

for 2012 were comparable to 2011 rates at Mehama, and comparisons at all sites showed the same highflow underprediction that was present with the 2011 data. During the low-flow season, the model 

significantly overpredicts streamflow at the Greens Bridge and Jefferson sites in 2012, a result that was 

not observed with the 2011 data; the difference is small, although it appears larger on the logarithmic 

scale of figures 11 and 12. The reason for this difference with the 2012 streamflow data is unknown. 

One possible source of the difference is the streamflow data from the Greens Bridge streamgage. 

Whereas streamflow data at the Mehama and Jefferson streamgages extend back to 1905 and 1907, 

respectively, streamflow data at Greens Bridge were collected from only 1964 to 1968, and again from 

2005 onward. The stage-discharge relationships used to calculate streamflow data tend to improve with 

time. Consequently, streamflow data from Green Bridge may not be as accurate as data from the other 

two streamgages. Other potential sources of the discrepancy include unknown summer streamflow 

withdrawals or poor estimates of summer streamflow withdrawals, streamside transpiration, or an 

increase in uncertainty related to the contributions of ungaged and unmodeled tributaries between the 

Mehama and Greens Bridge streamgages.

Figure 11. Measured and modeled streamflow for the North Santiam River at Mehama, Oregon (USGS 

streamgage 14183000), 2012. 
19 

Figure 12. Measured and modeled streamflow for the North Santiam River at Greens Bridge, Oregon (USGS 

streamgage 14184100), 2012. 

Figure 13. Measured and modeled streamflow for the Santiam River at Jefferson, Oregon (USGS streamgage

14189000), 2012. 

Table 6. Goodness-of-fit statistics using modeled hourly streamflows for two periods in 2012. 

[Abbreviations: ID, identification number; ME, mean error; MAE, mean absolute error; RMSE, root-mean squared error; MAPE, mean 

absolute percentage error;  ̊C, degrees Celsius]

Streamgage USGS ID ME MAE RMSE MAPE

(m3/s) (m3/s) (m3/s) (percent)

Calendar year 2012

Mehama 14183000 -16.5 17.1 27.2 10.5

Greens Bridge 14184100 -18.3 25.6 41.8 21.2

Jefferson 14189000 -39.5 54.4 110 18.8

June–October 2012

Mehama 14183000 -5.5 6.7 15.3 5.8

Greens Bridge 14184100 1.6 12.7 23.5 23.9

Jefferson 14189000 3.6 24.7 53.2 20.2
20 

A comparison of measured and modeled 2012 water temperatures at the Mehama, Greens 

Bridge, and Jefferson sites shows that the model adequately captured the patterns in the data (figs. 14, 

15, and 16, respectively), with goodness-of-fit metrics showing values that are similar to those from 

2011 for the two upstream sites, and just slightly higher errors at the Jefferson site (compare table 7 to 

table 4). Summer and early fall temperature errors for 2012 were comparable to those in 2011 at 

Mehama and downstream at Greens Bridge, but higher at Jefferson. The higher error values at Jefferson 

are likely due to the increase in uncertainty resulting from the estimated lateral inflows and temperatures

of the South Santiam River. All mean absolute error values were equal to or less than 0.7  ̊C for the 

periods of interest. This compares well with the North Santiam CE-QUAL-W2 river model developed 

by Sullivan and Rounds (2004), which resulted in absolute mean errors ranging from 0.5 to 1.0 °C. 

Figure 14. Measured and modeled mean daily values of temperature for the North Santiam River near Mehama, 

Oregon (USGS streamgage 14183010), 2012. 

Figure 15. Measured and modeled mean daily values of temperature for the North Santiam River at Greens 

Bridge, Oregon (USGS streamgage 14184100), 2012. 
21 

Figure 16. Measured and modeled mean daily values of temperature for the Santiam River near Jefferson, Oregon 

(USGS streamgage 14189050), 2012. 

Table 7. Goodness-of-fit statistics using modeled hourly temperatures for two periods in 2012. 

[Abbreviations: ID, identification number; ME, mean error; MAE, mean absolute error; RMSE, root-mean squared error; MAPE, mean 

absolute percentage error;  ̊C, degrees Celsius]

Streamgage USGS ID ME MAE RMSE MAPE

(m3/s) (m3/s) (m3/s) (percent)

Calendar year 2012

Mehama 14183000 -0.2 0.4 0.5 4.1

Greens Bridge 14184100 -0.3 0.5 0.7 6.0

Jefferson 14189000 0.4 0.6 0.8 7.1

June–October 2012

Mehama 14183000 0.0 0.4 0.6 3.3

Greens Bridge 14184100 -0.1 0.5 0.7 3.8

Jefferson 14189000 0.4 0.7 1.0 5.8
22 

A plot of measured temperature versus modeled temperature for both 2011 and 2012 show that 

errors are fairly well-distributed at Mehama (fig. 17A). The same figure shows a bias at high 

temperatures at Greens Bridge in 2011 (fig. 17B), as previously discussed. However, this bias did not 

appear in 2012. The reason for the inconsistency is likely the positive bias of summer streamflow 

associated with the 2012 model. Results similar to Greens Bridge are seen at Jefferson, although the 

2011 bias is not as strong (fig. 17C). 

Figure 17. Measured and modeled mean daily values of temperature for 2011 and 2012 at USGS streamgages on 

the North Santiam River, Oregon.
23 

Figure 17.—Continued
24 

Figure 17.—Continued
25 

Summary and Implications for Future Research and Monitoring

A river model of the North Santiam and Santiam Rivers was developed and calibrated to 

simulate streamflow and water temperature downstream of Detroit and Big Cliff Dams. Calibration was 

focused on 2011 conditions with particular interest on the June–November period. Hourly water 

temperature data were simulated with typical mean absolute errors from 0.4 to 0.8°C and little to no 

annual bias when compared to measured data, although bias levels are higher at specific locations 

during specific periods. A check using 2012 data in the model produced mean absolute errors ranging 

between 0.4 and 0.7  ̊C, with little or no bias at the Mehama and Greens Bridge streamgages, and a 

positive annual bias of about 0.4  ̊C at the Jefferson streamgage. The model tended to predict daily 

temperature averages with slightly more accuracy compared to the hourly data. 

The model predictions generally are less accurate for more downstream locations, especially 

downstream of the confluence with the South Santiam River. This is expected, as temperature data at the 

mouth of the South Santiam River were estimated using a statistical model based on measured 

temperatures 37 mi (60 km) upstream of the confluence with the North Santiam River. 

Much of the model’s temperature error is attributable to the model’s difficulty in fully simulating

diurnal variability in the summer. Although overall errors fall within desired limits (mean absolute error

less than 1.0 °C; mean error near zero), modeled summer water temperature maxima tend to show a 

small positive bias, especially at the downstream locations. The model simulated daily mean water 

temperature values to within acceptable limits. 

The model can predict water temperatures to within a mean absolute error of 0.8  ̊C over the 

low-flow summer and early fall period and can be used to estimate impacts on streamflows and 

temperatures for the length of the North Santiam River downstream of Big Cliff Dam under a series of 

potential future conditions in which structures and/or operations at Detroit and Big Cliff Dams are 

changed. Further model refinement would be needed to reduce the positive bias in the prediction of 

daily summer and early fall temperature maxima and the negative bias in the prediction of winter highstreamflow events. Future model calibration also could be conducted using temperature or streamflow 

values that fall outside of the range used in this study. 

Future model predictions could be improved with the availability of more streamflow and 

temperature data. Most useful to the improvement of the model would be temperature data near the 

mouth of the South Santiam River, which would eliminate the need for the statistical model built to 

estimate warming in that river between the Foster streamgage and its confluence with the North Santiam 

River. Other useful data that would improve the model include streamflow and temperature for the other 

modeled tributaries to the North Santiam River (Bear Branch Creek, Rock Creek) and measured

municipal withdrawal rates.

Further model refinement also may be possible with the addition of more meteorological data, 

specifically short-wave radiation and wind speed data. Wind speed is likely highly variable throughout 

the watershed, and more representative wind stations might produce more accurate simulations of 

evaporative cooling. Short-wave solar radiation reaching the water surface also may be highly variable 

in the watershed, especially for partly cloudy weather conditions, where cloud cover low in the valley 

may not be identical to that closer to the headwaters. However, even with a more dense distribution of 

short-wave radiation datasets, the lack of a shading algorithm in HEC-RAS version 4.1.0 limits the 

ability of the model to effectively simulate daily summertime diurnal water temperature variation. 

Future versions of HEC-RAS may incorporate a shading algorithm, which would eliminate the need for 

manually manipulating short-wave radiation data to emulate shading and produce more accurate solar 

heating of the water surface.
26 

Although the model is not intended for use in predicting high-streamflow events, additional 

calibration to account for small, ungaged tributaries could be implemented to reduce or remove the 

negative bias found during winter storm events. Additional considerations for summer sources and 

usage could improve summer streamflow estimates.

Acknowledgments

The authors thank Kathy Breen of the USGS Oregon Water Science Center for her assistance 

with figures used in this report. Discussions with Dan Turner and Kathryn Tackley of the U.S. Army 

Corps of Engineers were helpful in evaluating the performance and utility of the model. 

References Cited

Buccola, N.L, Rounds, S.A., Sullivan, A.B., and Risley, J.C., 2012, Simulating potential structural and 

operational changes for Detroit Dam on the North Santiam River, Oregon, for downstream 

temperature management: U.S. Geological Survey Scientific Investigations Report 2012–5231, 68 p. 

[Also available at http://pubs.usgs.gov/sir/2012/5231/.] 

Evans, E.C., McGregor, G.R., and Pettrs, G.E., 1998, River energy budgets with special reference to 

river bed processes: Hydrological Processes, v. 12, p. 575–595. 

Novak, C.E., 1985, WRD data reports preparation guide: U.S. Geological Survey Open-File Report 

1985–480, 331 p. 

Rounds, S.A., 2010, Thermal effects of dams in the Willamette River basin, Oregon: U.S. Geological 

Survey Scientific Investigations Report 2010-5153, 64 p. [Also available at 

http://pubs.usgs.gov/sir/2010/5153/.] 

Sullivan, A.B., and Rounds, S.A., 2004, Modeling streamflow and water temperature in the North 

Santiam and Santiam Rivers, Oregon, 2001–02: U.S. Geological Survey Scientific Investigations 

Report 2004–5001, 35 p. [Also available at http://pubs.usgs.gov/sir/2004/5001/.] 

Sullivan, A.B., Rounds, S.A., Sobieszczyk, S., and Bragg, H.M., 2007, Modeling hydrodynamics, water 

temperature, and suspended sediment in Detroit Lake, Oregon: U.S. Geological Survey Scientific 

Investigations Report 2007-5008, 40 p. [Also available at http://pubs.water.usgs.gov/sir20075008/.] 

U.S. Army Corps of Engineers, 2008, HEC-RAS river systems analysis user’s manual: Davis, 

California, U.S. Army Corps of Engineers, Hydrologic Engineering Center, Institute of Water 

Resources, 790 p., accessed August 16, 2014, at http://www.hec.usace.army.mil/software/hecras/documentation.aspx/.

U.S. Army Corps of Engineers, 2014, Hydrologic Engineering Centers River Analysis System (HECRAS): Website, http://www.hec.usace.army.mil/software/hec-ras, accessed August 15, 2014. 

U.S. Geological Survey, 2013a, StreamStats—Oregon: U.S. Geological Survey database, accessed 

December 19, 2013, http://water.usgs.gov/osw/streamstats/oregon.html. 

U.S. Geological Survey, 2013b, Tributary width surveys—Willamette River water temperature 

investigation: U.S. Geological Survey, accessed August 9, 2013, at 

http://or.water.usgs.gov/projs_dir/will_tmdl/width_survey.html. 
Publishing support provided by the U.S. Geological Survey

 Science Publishing Network, Tacoma Publishing Service Center

For more information concerning the research in this report, contact the

Director, Oregon Water Science Center

U.S. Geological Survey

2130 SW 5th Avenue

Portland, Oregon 97201

http://or.water.usgs.gov
Stonewall and Buccola—Development of a HEC-RAS Temperature Model for the North Santiam River, Northwestern Oregon—Open-File Report 2015–1006

ISSN 2331-1258 (online)

http://dx.doi.org/10.3133/ofr20151006